add plots on team model parameter changes since start of season

Author: jack89roberts

notebooks/team_model_bpl_next.ipynb

@@ -299,12 +299,116 @@
     "plt.title(team_a);"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Change since start of season"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model_team = get_fitted_team_model(CURRENT_SEASON, 1, session)\n",
+    "select_idx = jnp.array([list(model_team.teams).index(t) for t in CURRENT_TEAMS], dtype=int)\n",
+    "a_mean_1 = model_team.attack.mean(axis=0)[select_idx]\n",
+    "b_mean_1 = model_team.defence.mean(axis=0)[select_idx]\n",
+    "\n",
+    "model_team = get_fitted_team_model(CURRENT_SEASON, NEXT_GAMEWEEK, session)\n",
+    "select_idx = jnp.array([list(model_team.teams).index(t) for t in CURRENT_TEAMS], dtype=int)\n",
+    "a_mean_2 = model_team.attack.mean(axis=0)[select_idx]\n",
+    "b_mean_2 = model_team.defence.mean(axis=0)[select_idx]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, ax = plt.subplots(1, 1, figsize=(9, 9))\n",
+    "ax.set_aspect(\"equal\")\n",
+    "\n",
+    "for a_1, b_1, a_2, b_2 in zip(a_mean_1, b_mean_1, a_mean_2, b_mean_2, strict=True):\n",
+    "    plt.arrow(\n",
+    "        a_1,\n",
+    "        b_1,\n",
+    "        a_2 - a_1,\n",
+    "        b_2 - b_1,\n",
+    "        width=0.005,\n",
+    "        length_includes_head=True,\n",
+    "    )\n",
+    "plt.xlabel(\"attack\", fontsize=14)\n",
+    "plt.ylabel(\"defence\", fontsize=14)\n",
+    "\n",
+    "for idx, team in enumerate(CURRENT_TEAMS):\n",
+    "    #ax.annotate(team, (a_mean_2[idx] - 0.03, b_mean_2[idx] + 0.02), fontsize=12)\n",
+    "    ax.annotate(team, (a_mean_2[idx] - 0.02, b_mean_2[idx] + 0.005), fontsize=12)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "a_mean = np.full((len(CURRENT_TEAMS), NEXT_GAMEWEEK), np.nan)\n",
+    "b_mean = np.full((len(CURRENT_TEAMS), NEXT_GAMEWEEK), np.nan)\n",
+    "\n",
+    "for gw in range(1, NEXT_GAMEWEEK + 1):\n",
+    "    model_team = get_fitted_team_model(CURRENT_SEASON, gw, session)\n",
+    "    select_idx = jnp.array(\n",
+    "        [list(model_team.teams).index(t) for t in CURRENT_TEAMS], dtype=int\n",
+    "    )\n",
+    "    a_mean[:, gw - 1] = model_team.attack.mean(axis=0)[select_idx]\n",
+    "    b_mean[:, gw - 1] = model_team.defence.mean(axis=0)[select_idx]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig = plt.figure(figsize=(8, 8))\n",
+    "for a_team, b_team, team in zip(a_mean, b_mean, CURRENT_TEAMS, strict=True):\n",
+    "    plt.plot(a_team, b_team, marker=\"o\", label=team)\n",
+    "    plt.annotate(team, (a_team[-1] - 0.02, b_team[-1] + 0.01), fontsize=12)\n",
+    "plt.xlabel(\"Attack\")\n",
+    "plt.ylabel(\"Defence\")\n",
+    "plt.axis(\"equal\")\n",
+    "fig.legend(loc=\"outside lower center\", ncol=len(CURRENT_TEAMS) / 4, bbox_to_anchor=(0.5, -0.07))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig, ax = plt.subplots(1, 2, figsize=(16, 6), sharex=True)\n",
+    "for idx, team in enumerate(CURRENT_TEAMS):\n",
+    "    ax[0].plot(\n",
+    "        np.arange(1, NEXT_GAMEWEEK + 1),\n",
+    "        a_mean[idx],\n",
+    "        marker=\"o\",\n",
+    "        label=team,\n",
+    "    )\n",
+    "    ax[1].plot(\n",
+    "        np.arange(1, NEXT_GAMEWEEK + 1),\n",
+    "        b_mean[idx],\n",
+    "        marker=\"o\",\n",
+    "        label=team,\n",
+    "    )\n",
+    "ax[0].set_xlabel(\"Gameweek\")\n",
+    "ax[1].set_xlabel(\"Gameweek\")\n",
+    "ax[0].set_title(\"Attack\")\n",
+    "ax[1].set_title(\"Defence\")\n",
+    "fig.legend(loc=\"outside lower center\", ncol=len(CURRENT_TEAMS) / 2, bbox_to_anchor=(0.5, -0.15))\n"
+   ]
   }
  ],
  "metadata": {
@@ -323,7 +427,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.12.11"
   }
  },
  "nbformat": 4,